Deep Learning Engineer - Distributed Task-Based Backends

NVIDIA, the world leader in accelerated computing, is seeking a Senior to Principal level Deep Learning Engineer to revolutionize distributed backends for major frameworks like PyTorch, JAX, and TensorFlow. This role combines cutting-edge AI development with high-performance computing, focusing on scaling AI models across thousands of GPUs.

The position offers an opportunity to work with premier Deep Learning frameworks and task-based runtime systems like Legate, Legion & Realm. You'll be at the forefront of developing compiler optimizations, parallelization strategies, and performance debugging tools for large-scale AI models. This role is perfect for someone who combines deep technical expertise in distributed systems with practical machine learning engineering experience.

The ideal candidate will have 5+ years of experience, strong programming skills in Python and C++, and extensive knowledge of parallel and distributed programming, particularly with GPUs. You'll work directly with enterprise customers and collaborate across NVIDIA's teams to shape the future of distributed GPU computing.

This role offers competitive compensation ($148,000-$287,500 base salary) plus equity, and provides the flexibility of working remotely or from NVIDIA's Santa Clara office. You'll be part of a company that's transforming industries through AI and digital twins, working on challenges that directly impact the advancement of accelerated computing technology.

Join NVIDIA to help build the next generation of distributed AI systems, working with cutting-edge technology and some of the brightest minds in the industry. Your work will directly influence how AI models scale and perform across massive distributed systems, making a real impact on the future of AI computing.